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This paper summarises and outlined evidence for the economic framework developed in the book Planetary Economics. It maps out three domains of decision-making, each of which involves different actors, processes and for which our understanding rests on different theoretical foundations. Each operates at different scales of time and social entities: they are complementary, not competing, explanations of diverse economic phenomena. For this session, the paper will also tentatively map different economic theories on to this framework.

The paper will then explain the unique characteristics of energy and climate change issues which make all three domains simultaneously important, and indeed argue that the issues raised span all three domains in approximately equal measure. The paper will also suggest that understanding the different domains help to explain the extremes of cycles in international energy markets and the poor history of energy forecasting.

The paper will then outline lessons on the three corresponding pillars of policy and why any individual policy pillar has been in practice prone to failure. It will outline correspondingly the need for policy packages spanning all three are credible, economically efficient and environmentally effective – and hence, politically stable. The concluding part of this overview talk will touch on the international dimensions, in which each pillar would raise different aspects of international cooperation.

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Stern’s (2007) report has engendered an interesting methodological debate among climate economists. In evaluations of climate policy, assigning values to some key moral parameters (e.g. in the Ramsey formula, the pure rate of time preference δ and the elasticity of marginal utility of consumption η) weights the interests of future generations more or less strongly. This influences conclusions about the evaluation of damages and how imperative it is to respond to these damages.

In IPCC SAR WG3, Arrow et al. (1996) called the participants of this debate descriptivists and prescriptivists. Descriptivists like Hutt (1940); Manne (1995); Nordhaus (1994, 2008) think that, by appealing to (empirical) market data, they can avoid making their own value judgments. This view contrasts with prescriptivists (e.g. Arrow et al. 1996; Broome 1994, 2012; Dasgupta 2008; Stern 2007), who have argued that explicitly weighing the moral import of parameter assignments is an unavoidable part of addressing these types of long-term policy evaluations.

In this presentation, I have two contributions. First, I intend to help classify these methodologies among ethical theories, to help incorporate moral philosophical contributions. Second, in the case of the Ramsey framework, I introduce new worries for both the descriptive and prescriptive positions. These worries come from application of recent behavioral psychological theories: prospect theory and heuristic theory.

First, to understand the positions in a philosophical context, it is necessary to recognize that there is an important presupposition underlying the debate. I argue that economists have a particular metaethical orientation with respect to assigning values to such parameters: they are subjectivist.

I argue further that the two economic groups (descriptivist/prescriptivist) represent a disagreement between two subjectivist views: social constructivism and expert judgment. However, there are well-known economic problems with the descriptive methodology of assigning values to these moral parameters based on market data alone (Arrow et al. 1996; Broome 1994). First, we do not operate in a perfectly competitive market, and market distortions prevent price signals from reflecting the full social costs. Second, it is not clear that individuals make market decisions with consideration of future generations; it is much more plausible that individuals are acting on personal time preference. Third, we do not see safe assets with maturities on climate impact timescales.

To avoid these issues, one might suggest that the moral parameters in the Ramsey formula be investigated directly from market participants. There is a shortcut with η, for example, since under utilitarian assumptions, η characterizes both inequity aversion and risk aversion. Since the experimental paradigms for testing risk aversion for individuals are well-understood, one might try to reveal risk aversion from behaviour under risk.

My objection is that a psychological theory called prospect theory (Kahneman 2011; Kahneman and Tversky 1979) indicates that revealed risk aversion will not be appropriate for normative judgments about η. This is primarily because η considers the absolute value of changes in consumption (and in utility) whereas prospect theory suggests that individuals will view outcomes as changes from a neutral reference point. This means that prospect theory tells us that risk aversion elicitation will fail to provide normative guidance.

These worries might lead one to take the expert judgment methodology. However, such judgments are precisely the kind of judgments that Kahneman (2011) warns might be subject to heuristic evaluation. We might substitute more easily accessible quantities in for η. Instead of asking “What is the elasticity of marginal utility with respect to consumption [i.e. η]?” one could answer a question that is more easily answered, such as “What is the psychological value of imagining having different levels of consumption?” Affective responses to having a various restricted consumption patterns are easily accessible to guide the decision making process, but can distort it (Finucane 2000). It is also easier to comprehend one’s own response to consumption over time than to explicitly consider intergenerational distributions. This second worry should also be accounted for in expert judgment.

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Policy-makers currently face unprecedented challenges and uncertainty when taking decisions that simultaneously affect economic development, technology and the environment. A lack of consensus on the impacts of climate policy in this complex interacting system has paralysed the policy-making processes, and policy indecisiveness has generated stagnation in investment decision-making, at the core of economic development. It is not clear to policy-makers how to reconcile economic policy supporting growth with climate change mitigation, and it is not clear how effective policies are likely to be.

This paper argues that policy-making based on conventional equilibrium science and economics is not fine-grained enough to capture the complexities of real-world human behaviour and its diversity, leaving a wide uncertainty gap for policy-making. We suggest that the use of dynamical methodologies involving complexity science coupled to behavioural science with sophisticated uncertainty analysis can provide appropriate tools to understand policy issues that involve a high degree of cross-sectoral interaction and correlations between agents, even at the aggregate level. This is to be used in a feedback loop with researchers in policy and law, in order to test potential policy packages while assessing their feasibility in the policy process.

We describe how policy-related interactions between each of three critical interrelated areas: technological change, the macroeconomy, and the natural environment, could be dynamically represented in much greater detail, allowing better representation of feedback processes related to policy choice. We describe what impact these developments would have on our predictive power and ability to constructively inform coupled technology-economy-environmental policy-making aimed at addressing climate change. We identify three areas of environmental policy where the high degree of behavioural correlation (positive re-inforcing feedbacks) and/or behavioural diversity makes their analysis impractical using conventional methods, and where the application of this methodology could be determinant for gaining appropriate insight for policy making: (1) the analysis of green growth, (2) cross-sectoral impacts of sector specific policies (e.g. biofuels), and (3) the effectiveness of policy for emissions reductions in consumer based sectors (e.g. private transport). By providing a concrete example, we suggest how a wider adoption of this approach could provide a step change in our ability to address the complex policy problems raised by sustainability transitions.

A framework to manage national decarbonization regimes

D. Kammen (University of California Berkeley, Berkeley, United States of America), J. P. Carvallo, (University of California Berkeley, Berkeley, United States of America), P. Hidalgo-Gonzalez, (University of California Berkeley, Berkeley, United States of America)

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A framework to manage national decarbonization regimes

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There is widespread agreement that mitigating global warming to prevent disruptive climate change requires nations or regions to internalize the global externality of anthropogenic carbon dioxide emissions. The most straightforward approach is to establish a price on carbon emissions, either directly through a carbon tax or indirectly through a cap-and-trade market mechanism. Several studies attempt to find an “optimal” price of carbon that depends largely on intertemporal consumption preferences (notably discount rates) and the estimated “damage function” that changes in weather, crop yields, and productivity, among others,impose to the global economy. These models, however, provide little theoretical insight into the dynamics of the decarbonization transition and they cannot inform the consequences of different carbon prices in the evolution of a socio-technical system. Many jurisdictions are considering incremental carbon prices without acknowledging the existence of technological “tipping points” triggered by specific carbon prices that suggest stable but more aggressive earlier action. We use high temporal and spatial resolution model SWITCH(see, e.g. Mileva, et al., 2013; Carvallo, Hidalgo-Gonzalez, and Kammen, 2014) to study the effect of the trajectories of prices for carbon emissions on the evolution of power systems. We have developed this linear programming optimization tool and utilized it to examine energy and climate objectives for distinct models of four different regions: the Western U.S., China, Chile, and Nicaragua. For each of these regions we find a common pattern of non-additive effects of increasing carbon prices and non-linear/non-decreasing marginal abatement costs. Despite the significant differences in the current energy mix and local resources in these regions, we find that tipping points at ~$30/ton and ~$60/ton lead to significant ‘transformative phases’ in each system. Specifically, as these carbon prices are reached we observe significant changes in the energy investment portfolio that would not likely have taken place with simply small, incremental, changes in carbon prices. Our analyses for each particular region suggest significantly different socio-technical evolution pathways for each area depending on an initial choice of carbon prices and its interaction with other policies. For example, in Chile carbon prices below $30 favor entrance of natural gas, while higher prices make renewable energy sources economical but impose different operational restrictions in the grid that require a different set of investment decisions. In the case of China, a high-adoption of renewable energy stage and a carbon capture and sequestration stage are defined before and after a $10/ton price respectively, with major transmission infrastructure implications. We propose a framework of decarbonization regimes with four critical stages: an earlier stage of natural gas/nuclear replacement; a second stage with higher renewable energy penetration; a third stage defined by earlier retirement of coal plants; and a four stage with minimal marginal gains from higher prices. We use this framework to recommend appropriate supplementary environmental and technology policies to achieve mitigation goals.